Communication networks including wide area networks and cellular telephone networks include numerous devices such as mobile communication and computing devices that contain data collection functionalities such as positioning information obtained from global position systems, audio data, video data, meteorological data and proximity detection data for other objects in proximity to a given mobile device. In order to effectively collect data from multiple devices changing their physical location and therefore their registration with base stations and nodes within the communication network, an accurate index of the current location and data generation capabilities of each mobile device is required. Suitable indexing systems accommodate the physical movement of the mobile devices and the changing registration of the mobile devices within the communication network.
As the number of mobile devices can be large and can grow rapidly, the index structure has to scale to support efficient data collection from the multitude of mobile wireless devices. In current mobile computing networks, the indexing structure is generally centralized, and the base stations in these networks function only a frequency and channel allocation entities. One current system uses a spatio-temporal extension of an R-tree index that is maintained in a large central database. Data collection from selected mobile devices based on queries from a central entity in this system is inefficient as it requires centralized processing and back and forth communications between the mobile station controller and the mobile devices.